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From your description I can't tell which of two very different cases you are trying to model: Case 1 - The worker needs to be available for work at server1 during a specific time interval (like 10:00-11:00) then available at another location during another time interval. If that is the case, then using Renee's approach to make a "smart" resource that rejects seizes from other locations and possibly interrupts work in process at the end of a period. Case 2 - The worker will work at server1 during a specific time interval (like 10:00-11:00) then work at another location during another time interval. If that is the case, then you might just have the worker be totally autonomous and move around as desired. In this case perhaps the worker actually removes an entity from the server queue, works on it, and then sends it on when done, or replaces it in the queue if the worker must leave before completing the part. If you haven't already seen it I'd look at SimBit Moveable Operator

Hi, I like to count total number of entities types waiting in front of the servers.Say for example, i am having entity1,entity2,entity3.Each entity is produced from separate sources(source1,source2,source3 respectively) .I got 5 servers(S1,S2,S3,S4,S5). Entity 1 processed in S1-S3-S5 Entity 2 processed in S1-S2-S4 Entity 3 processed in S3-S4-S5 Each entity has different arrival rate. i like to create a expression to sum the total number of entity type 1 waiting in queue infront of the servers S1-S3-S5.if total number of entity type 1 waiting is greater than 100 numbers,the next coming entity type 1 from the source1 should leave the whole system( i mean sink without processing)similarly i like to count for entity2,entity3. Can anyone help me out? Thanks, R

This is my first time using this forum so I hope I am posting this in the correct section. I am currently busy with a problem involving the dust suppression program at an open pit mine. In open pit mines water trucks are used to maintain the condition of haul roads and reduce mine dust. Water trucks load water from refilling stations and traverse the road to spray water. After the water is exhausted, the water truck travels toward one of water stations for refilling and then continues to traverse the roads to satisfy the watering patterns. The water trucks run 24 hours per day.In practice the watering frequency of each road is related to the traffic intensity of haul trucks. The period of effectiveness, after the road has been watered, can range from 30 minutes to 3 hours. Regular light watering at approximately 0.3-0.5l/m2 is much more effective than infrequent heavy watering. To simplify the problem each road will be assigned a watering frequency (e.g. every 60 minutes) and a sliding time window (e.g. 10 minutes). The water can therefore be sprayed on the road within the given time window (e.g. 50 to 70 minutes). If the trucks service the road more frequently than every 50 minutes the road will be over watered and this can cause a host of problems. If the trucks water the road less frequently than every 70 minutes dust aggregation will start becoming problematic. In order to satisfy the water demand of the roads, it is possible that a truck waters a road segment first, then travels along the next road segment without watering it, and then waters another road segment. The road segment that a water truck traverses without watering is called a dead heading. A bidirectional road has to be watered in each of the two directions Empty water trucks are refilled at the refilling stations. A refilling station can serve a limited number of trucks at the same time. Also, a limited number of trucks can wait before being refilled. Hence, every refilling station has two kinds of capacities: the capacity for refilling the trucks and the capacity for holding trucks. If a refilling station is overloaded, some trucks need to be reassigned to a different refilling station. My main problem at this stage is how to model the dust aggregation on the haul roads. I started by setting up each road as a source server sink and then only displaying the server queue. The entities can then be modeled as dust clouds. The trucks then tend to the servers as operators. This still does not give the desired outcomes. I’m struggling to schedule the trucks to move on the shortest route and then return to the nearest filling station once they have depleted their water supply. Does anyone have any other ideas on how to approach the problem? Thanks for your help! Regards Carl-Gustaf Gericke